قائد فريق - مهندس ذكاء اصطناعي

Lead AI Engineer (Python / LLM / Agentic AI)

Job Description

We are looking for an experienced Lead AI Engineer to design, develop, and deliver production-ready AI applications and backend services.

The ideal candidate combines strong Python backend engineering skills with hands-on experience building LLM-powered applications, AI agents, and intelligent automation solutions.

Key Responsibilities

• Design, develop, and maintain scalable backend services and AI-powered applications using Python
• Design and implement AI agents and agentic workflows, including tool calling, orchestration, multi-step reasoning, and multi-agent collaboration
• Build LLM-powered solutions using RAG, embeddings, vector databases, and structured outputs
• Integrate LLMs with internal systems, enterprise APIs, and external services using MCP and other integration approaches
• Evaluate and optimize AI solutions for accuracy, reliability, performance, latency, and cost
• Design scalable architectures using asynchronous processing, message queues, caching, and event-driven patterns
• Implement AI security controls, including prompt injection protection, data privacy, access control, and safe tool execution
• Build and deploy production-ready services with proper testing, monitoring, logging, and error handling
• Collaborate with product and engineering teams to translate business requirements into technical solutions
• Lead technical design discussions, review code, mentor engineers, and establish engineering best practices
  
  

Requirements

Job Requirements

Required Qualifications

• 7+ years of professional software engineering experience, including at least 2 years of backend development using Python
• Strong experience with Python, FastAPI, asynchronous programming, and Pydantic
• Hands-on experience developing and deploying LLM-powered applications in production
• Practical experience with AI agents, tool/function calling, and agent orchestration frameworks, such as LangGraph, LangChain, or equivalent solutions
• Strong understanding of RAG architectures, embeddings, semantic search, and vector databases
• Experience integrating LLMs through APIs, including structured outputs, prompt engineering, and handling model failures
• Experience evaluating LLM applications, including response quality, hallucinations, reliability, and performance
• Solid understanding of distributed systems, message queues, caching, retries, idempotency, and persistent state management
• Experience with PostgreSQL, Redis, Docker, and REST APIs
• Strong knowledge of automated testing, clean architecture, design patterns, and code quality practices
• Experience designing and delivering major features or products from concept to production
• Strong analytical, troubleshooting, communication, and technical leadership skills
• Experience with Model Context Protocol (MCP) and building MCP servers or clients
• Experience with advanced agent orchestration, multi-agent architectures, and human-in-the-loop workflows
• Experience with Qdrant, pgvector, Pinecone, or similar vector databases
• Experience with NATS, Kafka, or other event-driven messaging technologies